For hearing loss, a clinically proven method to increase speech intelligibility in ambient noise is to provide the user with directional hearing instruments. In general, directional microphone systems are configured as either endfire or broadside. In (freefield) endfire configurations, the maximum response angle (MRA) can point to either 0° for the case of a unidirectional response, to 180° for the case of an inverted unidirectional, or to both in the case of a bidirectional (figure of eight). It is not possible to shift the MRA of a (freefield) endfire unidirectional to any other angle, regardless of signal processing. When a forward-pointing unidirectional is worn in-situ, the MRA shifts from its freefield value of 0° to a different angle based on head and torso acoustical scattering; it is still not possible to shift its MRA any other forward-pointing angle via signal processing. In (freefield) broadside configurations, the MRA can be shifted to any angle, however, the shiftable frequency range is related to the separation distance of the outer microphones. For in-the-ear (ITE) and behind-the-ear (BTE) hearing instrument applications, this separation distance is too small to provide any substantive directionality. Consequently, broadside directional microphone systems have not been used by manufacturers of hearing instruments, with the exception of some integrated eyeglass devices described in technical research papers. It would be advantageous, therefore, to have the ability to shift and control the MRA of a hearing instrument.
One figure of merit used to benchmark the directional gain of a hearing instrument is the Directivity Index (DI). The DI can be regarded as a Signal-to-Noise Ratio (SNR) captured under two different acoustical conditions. In the first condition, the ‘signal’ is computed from acoustic energy arriving from the front 0° angle (i.e., on-axis target direction); this condition can be simulated only in a perfectly anechoic space. In the second condition, the ‘noise’ is computed from isotropic energy (i.e., temporally uncorrelated planar wavefronts arriving with equal amplitude from all directions); this condition does not exist physically and can only be simulated in: 1) a sufficiently reverberant field in which case the isotropic noise estimate is the temporal average of a single measurement of incoherent wavefronts, or 2) an anechoic space with a loudspeaker positioning/scanning apparatus in which case the isotropic noise estimate is the spatial average of multiple measurements of coherent wavefronts. It is interesting to note that the DI is computed under conditions that the user will never encounter; these conditions are used simply because they can be reproduced with relative ease in any laboratory setting—thereby providing a level playing field for manufacturers to compute a DI and benchmark the directional performance of their product.
An optimized DI in isotropic noise (sometimes referred to as a spherically ‘diffuse’ field) is 6 dB. In other words, the highest directional gain that can be achieved in a spherically-diffuse field for a 1st-order differential microphone is 6 dB. The only environments with excessively-reverberant fields (T60≈10 seconds) that remotely approach the statistical properties of a spherically-diffuse field exist in laboratories accredited for standard ASTM C423 or ISO 3741 measurements. Typical indoor environments (T60≈1 second) encountered by a hearing-instrument user have been described as ‘cylindrically’ diffuse, i.e., the reverberation arrives at the user from all walls of the room while the floor and ceiling reflections are attenuated due to carpet and sound-absorptive suspended ceiling tiles. The highest theoretical directional gain achievable in a cylindrically-diffuse field for a 1st-order differential microphone is 4.8 dB. The DI as measured in a laboratory environment, therefore, yields a biased estimate of the actual directional gain for a user in a typical indoor environment. To recapitulate, an anechoic or spherically-diffuse acoustical environment is unique to a laboratory; a real-world reverberant environment is not spherically-diffuse and has properties ranging somewhere between anechoic and spherically-diffuse. It would, therefore, be advantageous to process the microphone signals of a hearing instrument in order to estimate the type of environment the user is exposed to: Is it cylindrically diffuse, or better yet, what direction does the majority of ambient noise arrive from? Such an estimate could provide a better procedure for controlling the instantaneous directional response of the hearing instrument.
There are a number of additional benchmarks that have been used to characterize the directional performance of microphone systems. Intrinsically, these benchmarks are based on various free-field sound energy ratios and are expressed either as decimals or decibels. One laboratory benchmark is the Unidirectional Index (UI) expressed as the dB ratio of average sound energy arriving from the user's front half sphere to the average sound energy arriving from the user's rear half sphere. Another laboratory benchmark is the Front to Total Random (FTR) ratio expressed as the decimal ratio of average sound energy arriving from the user's front half sphere to the average sound energy arriving from all directions. In addition to the free-field energy ratios, there are a number of 1st-order directional sensitivity patterns typically referenced by manufacturers; these patterns include the hypercardiod which optimizes the DI and the supercardioid which optimizes the FTR. Each optimization is assumed in a spherically-diffuse field. For reference, a table summarizing the properties of these polar patterns is shown in FIG. 1. It is interesting to note that a bidirectional polar pattern has the same DI as a cardioid polar pattern, and the same FTR as an omni, thereby revealing the limitations of a DI or FTR alone to benchmark directional behavior and performance. Only in their entirety and relation are these benchmarks definitive.
In addition to the above-referenced benchmarks related to spherically or cylindrically-diffuse fields, there are benchmarks that are independent of the acoustical environment and capture intrinsic directional performance. For example, the −6 dB point of the primary directional lobe is a performance parameter that is independent of a spherically-diffuse or cylindrically-diffuse environment. Similarly, the sensitivity ratio at 180° to the sensitivity at 0° is independent of the acoustical environment. Such benchmarks do not require a spatial integration of sound energy, they're simply the measured response ratio of wavefronts arriving from certain directions. Thus, a cardioid polar pattern is a cardioid polar pattern, regardless of what environment it is in. The directional gain it provides to the user, however, is a function of the amount of ambient noise and the direction from which it arrives—relative to the spatial orientation of the polar sensitivity pattern. It would be advantageous, therefore, to compare the relative sound energy estimates from a number of (in-situ) fixed, directional polar responses to predict the properties of the user's acoustical environment. The simplest fundamental approach is to estimate the ambient sound energy arriving from the front (−90°→90° in azimuth), the left)(180°→360°, the right)(0°→180°, and the rear)(90°→270°, where 0° is synonymous with 360°.
It was noted previously that real-world acoustic environments are not spherically diffuse. For this reason, it seems rather specious that directivity indices optimized for spherically-diffuse conditions have been used exclusively to predict directional benefit of hearing instruments. A clinical question often asked is: What is the best pattern for the user? The answer should begin with another question: What acoustical environment is the user in? More specifically, where is the target and where is the ambient noise? Certainly, a person driving a car who is trying to hear speech from a passenger in the front seat would benefit more from a right-pointing cardioid than a forward-pointing hypercardioid (except in England, of course). For this reason, it would be advantageous to have a directional processing system that could estimate both the location of the target signal and direction of incoming ambient noise, and adjust the user's audio signal by controlling the MRA and optimizing the SNR with a polar pattern for each particular acoustical environment—regardless as to whether the ambient noise is spherically-diffuse, cylindrically-diffuse, or anything in between. The simplest fundamental approach could assume that the target is always at 0° on-axis, and that the ambient noise is predicted from the energy estimates described previously.
Traditionally, two approaches have been used to adjust the SNR for a hearing instrument. The first approach compares the output signals of both an omnidirectional microphone and a separate differential directional microphone. These two signals alone are used to control an algorithm to switch the audio output from omnidirectional mode (typically used in quiet environments) to directional mode (noisy environments) via a simple linear or logarithmic pan. This approach has been referred to as ‘dynamic’ directionality. It is robust in that the output signal from the 1st-order differential microphone provides a directional polar pattern that is very stable to electroacoustical drift. It is limited in that only two estimates are used in controlling the switch from omni to directional modes. For this reason, it would be advantageous to use additional sound energy estimates to characterize the user's acoustical environment and adjust the final polar pattern provided to the user.
The second approach uses two omnidirectional mics in an endfire configuration. The output signal of either mic provides the omnidirectional mode and the output signal of the rear mic is inverted, temporally delayed, and summed with the front mic to provide a static, directional mode of operation. With DSP, the temporal delay can be adjusted to shift the null angle of the polar pattern until a certain signal (usually the omni output) to noise (usually the inverted, delayed-and-summed output) ratio is optimized. This approach has been referred to as ‘adaptive’ directionality. It is robust in that the actual polar pattern provided to the user doesn't need to be known computationally; the algorithm simply adjusts the time delay until a null is steered to some noise source (jammer) and a certain SNR estimate is reached. It is limited in that the target is typically assumed to be 0° on-axis and the electrical mismatch of the front and rear channels (dominated by electroacoustical mismatch of the mics) needs to be tightly controlled. To remedy mic mismatch due to drift, elaborate schemes for in-situ mic matching have been patented; marketing literature for adaptive directionality typically includes references to these proprietary schemes.
In general, mic mismatch manifests itself in a 1st-order endfire configuration as follows: sensitivity mismatch degrades the null and phase mismatch shifts the null angle. If mismatch is not managed properly, the directional algorithm can mistakenly shift the null to the 0° on-axis target or the algorithm can lose its ability to provide any semblance of a null altogether. For a 1 cm spaced endfire hypercardioid in a spherically-diffuse field, FIG. 2 shows the independent sensitivity mismatch (0.6 dB at 500 Hz) that would yield 2 dB degradation in the DI and the independent phase mismatch (constant time delay of 22 μsec) that would shift the null angle to 54° off-axis (i.e., a supercardioid pointing backwards).